1. Field of the Invention
The present invention relates primarily to physiological nonlinear dynamical system control. More particularly, the present invention involves a system and method to predict and prevent seizures caused by neurological dysfunction.
2. Discussion of the Related Art
Epilepsy is a chronic disorder characterized by recurrent brain dysfunction caused by paroxysmal electrical discharges in the cerebral cortex. If untreated, an individual afflicted with epilepsy is likely to experience repeated seizures, which typically involve some level of impaired consciousness. Some forms of epilepsy can be successfully treated through medical therapy. However, medical therapy is less effective with other forms of epilepsy, including Temporal Lobe Epilepsy (TLE) and Frontal Lobe Epilepsy (FLE). With TLE and FLE, removing the portion of the hippocampus and/or cerebral cortex responsible for initiating the paroxysmal electrical discharges, known as the epileptogenic focus, is sometimes performed in an effort to control the seizures.
Although this discussion substantially focuses on epileptic seizure, it will be apparent to one of ordinary skill that the discussion may also apply to any other dynamical disorders of the brain, such as Parkinson's Disease, migraines and schizophrenia, as well as of other physiological systems that involve internal pathological (malfunctioning) control.
Related art approaches to seizures generally involve either detection of a seizure in its early phases, or prediction of seizure onset. Detection approaches generally measure neural activity using electroencephelography (EEG) and identify spikes in EEG data (or some other anomaly) that are consistent with the onset of seizure. Prediction is more sophisticated, whereby certain sites of the brain are measured and characterized, either structurally or functionally, and the measurements or characterizations are correlated with known conditions that signal impending seizure.
For prediction, functional measurement and characterization of brain sites generally identify changes in neural activity at certain brain sites, and predict the onset of seizure by correlating specific measured neural behavior with known indicators of seizure onset. Structural measurement and characterization of brain sites include identifying changes in the impedance of brain tissue between electrodes. Changes in impedance between particular brain sites may be correlated with the onset of seizure in certain patients. Other approaches include comparing signal propagation delay times between different brain sites.
Structural and functional approaches to prediction of seizure onset may involve either passive or active measurements, or a combination of both. Active structural measurements generally involve applying a known signal stimulus and measuring the signal after propagating through a portion of the brain to determine parameters such as impedance. Active functional measurements generally involve applying a known stimulus signal and measuring a change in neural behavior of a given brain site in response to the applied signal.
Certain related art functional approaches to prediction include measuring and characterizing the chaoticity of certain brain sites, and identifying entrainment between a pair of brain sites. As disclosed in U.S. Pat. No. 6,304,775 to Iasemidis et al., identifying entrainment between brain sites can provide notice of seizure susceptibility hours, if not days, before seizure onset.
For detection, EEG data is generally processed to identify the early stages of a seizure through traditional signal processing algorithms, such as frequency domain, wavelet, and neural network implementations. The results of such processing are compared with predetermined thresholds to identify seizure onset.
Although related art methods have demonstrated the ability to predict the onset of seizure, an equally sophisticated method for effective control is lacking. For example, many related art prediction systems, having predicted the onset of a seizure, generally attempt to mitigate the seizure by methods such as releasing anti-seizure medication into the patient's bloodstream, applying high amplitude electrical shocks to the relevant brain sites, or applying sensory stimuli (such as visual) to the patient, all of which are traditional treatment methods.
Certain related art approaches to control seizures involve the use of stimulation based on prediction of onset, so that the stimulation may be more effective in preventing epileptic seizure. In other words, the earlier the prediction, the more effective the prevention. U.S. Pat. No. 6,671,555 to Gielen et al, uses an active measurement technique to measure functional connectivity of the brain; correlates a decrease in functional connectivity with seizure onset; and applies high frequency pulses to prevent the seizure before it occurs. Apparent drawbacks of this approach are as follows: the estimation of the connectivity measure requires high levels of signal injection, especially since the estimation must be done quickly; and the correcting signal (pulses) is generic and coarse. Accordingly, excessive stimulation power is generally required, and there may be cases where such stimulation is ineffective. Published U.S. Patent Application, Publication No. 2005/0021104 by DiLorenzo mentions the use of control laws to apply feedback stimuli to brain sites based on detected neural activity, but does not address how to use feedback to take advantage of the chaotic nature of neural activity, or how to use control with prediction in order to prevent a seizure before it starts.
Other related art approaches to seizure mitigation involve open loop application of signals in a preprogrammed manner. Examples of open loop approaches include continuously stimulating the vagus nerve or the thalamus with predetermined stimulation signals. Generally, open loop approaches do not involve any sensing and predicting of seizures and only stimulate the brain to prevent seizure. As such, they are expected to be less effective and less efficient than closed-loop approaches.
In all of the cases described, seizure mitigation or control is generally primitive compared to the state of related art approaches to prediction. In other words, although considerable insight has been gained into neural structure and function related to predicting seizures, mitigation and control approaches do not take advantage of this insight and instead rely on more traditional treatments.